Reducing burden of disease from residential indoor air exposures in Europe (HEALTHVENT project)
Manuscript: 1476-069X-14-S1-S6 (Healthy-Polis special issue)
Reviewer: James Milner
Recommendation: Revise
General comments
This paper attempts to understand optimal ventilation rates at the national level across 26 European countries and to contrast the benefits of optimizing ventilation with filtration of outdoor air pollution and control of indoor sources. This is an important topic given the key role of the housing sector in tackling both air pollution and climate change. Although the methods used are relatively simplistic, they are appropriate for analyses performed at the scale presented in the paper. The findings and conclusions are well supported by the results. I would therefore support publication. However, I believe the manuscript would benefit from a stronger statement of the aims of the work and some clarifications regarding the methods (see below).
My main concern relates to the assumption made by the authors that indoor-generated PM2.5 is equally as harmful to health as outdoor-generated PM2.5. There is little evidence to support this (though it is quite a commonly made assumption). I would like to see some form of sensitivity analysis in relation to this assumption, since it may have an impact on the final results (though probably not on the ultimate conclusions).
More detailed comments can be found below. I consider the suggested revisions to be relatively minor.
Specific comments
1. Is the question posed original, important and well defined?
The research question posed by the paper is important and I believe the methods used are appropriate to answer it. However, the aims of the paper are not currently well stated (in both the main text and in the abstract). The main statement of the aims comes towards the end of page 5, which states “This work aims to summarize the current understanding of the sources of health risks in indoor environments and their relationship to ventilation requirements”. This doesn’t really capture what the authors have actually done. There is a slightly better statement of the aims hidden in the Methods (top of page 7) but even this doesn’t quite feel sufficient.
2. Are the data sound and well controlled?
Yes, although the source of some of the input data can be made clearer in the text, especially in relation to Table 2 (see below).
3. Is the interpretation (discussion and conclusion) well balanced and supported by the data?
Yes.
Reviewer 1
4. Are the methods appropriate and well described, and are sufficient details provided to allowothers to evaluate and/or replicate the work?
The methods are generally well described. However, I have a few specific issues (see the additional comments below).
5. What are the strengths and weaknesses of the methods?
The methods are based on relatively simplistic tools (both the mass-balance exposure model and the risk/health impact model). However, I think they are appropriate for the type of analysis presented in the paper.
My main concern relates to the assumption of equal health risk associated with both outdoor- and indoor-generated PM2.5. The authors discuss this briefly in the Discussion section but this assumption is highly uncertain since almost all of the published epidemiology is based on outdoor PM2.5. The paper would benefit from greater emphasis on the sensitivity of the results to this assumption. Perhaps, the analysis (or part of it) could be repeated without the effects of indoor-generated PM2.5 or with a reduced exposure-response coefficient?
6. Can the writing, organization, tables and figures be improved?
Although the manuscript is generally well written, there are reoccurring problems, most importantly missing articles throughout the paper (e.g. a, the). For instance, in the abstract, “Based on measurements of the European Environment Agency (EEA),…” and “A framework for developing European health-based ventilation guidelines…” would be preferable. I realise that English is not the authors’ first language (and, again, I should stress that most of the language used is very good). However, I think the paper would benefit from a thorough edit by a native English speaker.
Also, the figures appear to be quite pixelated and may not be in an appropriate format for publication.
7. When revisions are requested.
No preference.
8. Are there any ethical or competing interests issues you would like to raise?
None.
9. Additional comments
• I believe the abstract would benefit from a little editing. At present, the Background section feelsunnecessarily long and there isn’t enough detail in either the Methods or Results sections. Themethods used for the health impact calculations aren’t mentioned at all, despite being key to thepaper. At the moment, I don’t feel the main results are clearly stated in the abstract.
• The paper refers throughout to “optimization”. I think a mathematician might object to the use ofthe term because the method doesn’t actually use a formal optimization process. I don’t thinkthis is too much of a problem but I do think a clear statement of what the authors mean byoptimization would be helpful (e.g. in the Methods). As I understand it, the “optimal” ventilationrate is just taken to be the one for which the health burden is smallest.
• I found some parts of the description of the risk model confusing, in particular towards thebottom of page 7. Firstly, the text states that the models are based on a predefined populationattributable burden of disease for each exposure and disease. Is this simply referring to thecalculation described later in the section (bottom of page 8)? Secondly, the text then states that“national estimates are then calculated from the national burden of disease data by scaling theattributable fraction according to the ratio of national versus European indoor concentrationestimates for each pollutant”. I’m afraid I could not follow the point being made here. Which“European” estimates are being referred to?
• On page 8 it is stated that “Traditional risk assessment methods estimate these [mortality andmorbidity] separately as numbers of cases”. I don’t really agree with this statement. There aremany health impact assessment methods which can consider both together and which are notincidence-based.
• The source of the data presented in Table 2 was not clear to me. Do these values relate toprevious work by the authors? The source(s) used should be explained and appropriatereferences provided.
• The section describing the basis for the assumed source control levels (page 11) can be improved.Although the authors provide an explanation of the methods that can be used to achieve suchsource control for each pollutant, it is not clear how the specific reduction % was decided upon ineach case. Are the reductions based on evidence or just plausible best guesses? For example,how do you know that implementing compulsory alarms will reduce CO sources by exactly 90%?The section would benefit from additional references to supporting literature.
• I do not understand why the source control scenario (scenario 3) did not also include an elementof ventilation optimization. The start of the section describing the scenarios suggests thatventilation optimization would be “complemented” first by filtration and then by source control(page 9). This suggests that a ventilation optimization component would appear in all scenarios.Choosing just one “optimal” ventilation rate makes it difficult to ascertain the relative benefitsdue to ventilation and source control.
• There is a line on page 14 which states “substantial reductions have been proposed in the earlierwork within the EU funded IAIAQ project”. It is not clear what reductions are being referred tohere. Is it reductions in the burden of disease due to indoor exposures? Why have reductionsbeen proposed?
• The term “EU-26” is used throughout the paper and should be defined somewhere.
• There are two occasions where references are missing in the text (bottom of page 8 and belowTable 3).
Dear Sotiris Please find my detailed comments on the attachment and my review below:
The manuscript "Healthy-Polis 1476-069X-14-S1-S6" focusses on the calculation of the annual burden of disease caused by exposure to indoor air pollution. This is very important work, given that the indoor environment is greatly ignored in relation to health. The MS is generally well written and certainly merits publication.
Apart from some minor editing, as indicated in the attachment, my comments mainly aim to improve the reader's understanding. The areas requiring clarification are highlighted in the attachment together with some comments. The two most important ones are as follows:
1. Methods: My understanding is that the exposure analysis refers only to indoor exposure in theresidential environment, without considering any time spent outdoors or in other indoor microenvironments; however, this is not clear in the text. Can you please clarify what the building stock represents.
2. The section on the "Risk model" directs the reader to several references of previous work.However, the reader may not be familiar with these methodologies and, most importantly, this significant part of the paper should stand alone. To enable a more friendly reading, the authors are kindly required to provide the data used in the methodology, step by step, as supplementary data (i.e. BoD, national estimates/statistics, PAF etc).This would improve a lot the quality and value of this publication.
Many thanks
Sani
Reviewer 2
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Reducing burden of disease from residential indoor
air exposures in Europe (HEALTHVENT project)
Arja Asikainen1§
, Paolo Carrer2, Stylianos Kephalopoulos
3, Eduardo de Oliveira
Fernandes4, Pawel Wargocki
5, Otto Hänninen
1
1 National Institute for Health and Welfare, Department of health protection,
Neulaniementie 4, 70210 Kuopio, Finland
2 University of Milan, Department of Occupational Health, Via G.B. Grassi 74,
20157 Milan, Italy
3 European Commission, Joint Research Centre, Via Enrico Fermi 2749, I - 21027
Ispra, Italy
4 University of Porto, INEGI, Rua Dr. Roberto Frias, 4200 400 Porto, Portugal
5 Technical University of Denmark, International Centre for Indoor Environment and
Energy, DTU Civil Engineering, 2800 Kps. Lyngsby, Denmark
§Corresponding author
Email addresses:
EOF: [email protected]
- 2 -
Abstract
Background
The annual burden of disease caused by inadequate indoor air quality is estimated to
correspond to a loss of over 2 million healthy life years in the European Union (EU).
This burden is caused by sources of indoor air pollution, including polluted outdoor
air used to ventilate indoor spaces. Based on measurements of European Environment
Agency (EEA), approximately 90% of EU citizens live in areas where the World
Health Organization (WHO) guidelines for air quality for particulate matter sized <
2.5 mm (PM2.5) are not met. Because sources of pollution reside in both indoor and
outdoor air, selecting the most appropriate ventilation strategy to ensure that the
health risks associated to exposure inside buildings are reduced is not simple and
straightforward task.
Methods
Framework for developing European health-based ventilation guidelines was created
in 2010-2013 in the EU-funded HEALTHVENT project. As a part of the project
potential of efficient control policies to reduce the burden of disease caused by indoor
exposures was estimated. Analysis was based on scenario comparison using a model,
which was based on mass-balance framework and changes in ventilation level.
Results
The quantitative comparison of three main policy approaches, (i) changing
ventilation rates only; (ii) filtration of outdoor air; and (iii) indoor source control,
showed that all three approaches are able to provide substantial reductions in the
health risks varying from approximately 20% to 44%, corresponding to 400 000 and
900 000 saved healthy life years in EU-26.
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Conclusions
Health effects of indoor air exposures can be decreased by increasing ventilation and
the present modelling shows that controlling indoor air sources plays a major role
when selecting appropriate ventilation rate. In a case where indoor sources cannot be
removed or their emissions cannot be limited to an accepted level, ventilation needs to
be increased to remove remaining pollutants. In these cases outdoor air pollution
become the major source of pollution in indoors, and it needs to be taken into account.
Particulate matter, mainly coming from outdoors to indoors, is the main cause of
health effects of indoor exposures in all European countries.
Background In the period 2006-2010, focus on indoor air quality has been raised by WHO, who
has issued specific guidelines addressing air exposure in indoor spaces [1, 2]. Already
during the previous two decades WHO had coordinated systematic reviews of
scientific evidence and set Air Quality Guidelines [3, 4] although not specific for
indoor air.
Requirements for indoor air quality (IAQ) in buildings is prescribed by existing
standards for ventilation, but are often poorly related on health. At present many
ventilation standards (e.g. EN15251 [5]) define ventilation requirements in non-
industrial buildings to meet comfort requirements of occupants, specified by the
percentage of dissatisfied persons with indoor air quality and/or by the intensity of
odour. While comfort is an important outcome, it does not fully reflect more serious
health impacts like asthma, allergies, chronic obstructive pulmonary disease,
cardiovascular diseases, lung cancer and acute toxication that are caused by exposures
to pollutants present in indoor air. There are no European guidelines which
recommend how the buildings should be ventilated to reduce the health risks of the
occupants’ exposed to indoor air pollutants.
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Direct scientific evidence on the relationship between ventilation and health is quite
limited. Wargocki et al. (2002) [6] reviewed 105 papers published in peer-reviewed
scientific journals, out of which 30 papers were judged to provide sufficient
information on ventilation, health effects, data processing, and reporting. Ventilation
was considered to be strongly associated with comfort (perceived air quality, PAQ)
and health (including sick building syndrome (SBS) symptoms, inflammation,
infections, asthma, allergy, and short-term sick leaves), and an association between
ventilation and productivity (performance of office work) was indicated.
Similar results were obtained in the review by Seppänen et al. (2004) [7]. They
concluded that the existing literature indicates that ventilation has a significant impact
on several important human outcomes including: (1) communicable respiratory
illnesses (disease prevalence or sick days); (2) sick building syndrome (SBS)
symptoms; (3) task performance and productivity, and (4) perceived air quality (PAQ)
as judged by building occupants or recruited sensory panels of assessors; and (5)
respiratory allergies and asthma.
Li et al. (2007) [8] performed a systematic review of the role of the built environment
in the transmission of airborne infectious agents. Specifically, they examined whether
there was sufficiently strong evidence in the current literature to substantiate a
contributory role of ventilation rates and airflow patterns in the airborne transmission
of infectious agents in different indoor settings. They concluded that there is strong
evidence substantiating the association between ventilation, air movements in
buildings and the transmission/spread of infectious diseases such as measles,
tuberculosis, chickenpox, influenza, smallpox and severe acute respiratory syndrome
(SARS).
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Sundell et al. (2011) [9] identified 27 papers published in peer reviewed journals
providing sufficient information on both ventilation rates and health effects. Multiple
health endpoints showed similar relationships with ventilation rate and were
biologically plausible, although the literature did not provide clear evidence on
particular agents. Higher ventilation rates in offices, up to about 25 l/s per person,
were shown in the reviewed literature to be associated with reduced prevalence of
SBS symptoms. Limited data suggested that inflammation, respiratory infections,
asthma symptoms and short-term sick leave increase with lower ventilation rates.
Home ventilation rates above 0.5 air changes per hour (h-1
) were shown in the
reviewed papers to be associated with reduced risk of allergic manifestations among
children in a Nordic climate.
None of the studies included in the reviews specifically addressed the role of outdoor
air quality on indoor exposures, even though 90% of EU citizens live in areas where
the WHO guidelines for air quality for PM2.5 is not met [10]. Neither was the
existence of indoor air sources systematically analysed nor exposure levels quantified
or considered when associating ventilation and health. Therefore the support from
these previous studies on determining the best combination of source control and
ventilation levels is limited. This work aims to summarize the current understanding
of the sources of health risks in indoor environments and their relationship to
ventilation requirements. The methods presented here allow for informed health-based
optimization of efforts aimed at reducing harmful exposures and improving health of
the occupants. The results are intended for development of national and international
guidelines and standards, and can also be used as background information when
analysing indoor air quality related issues in buildings.
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Methods
Exposures
Ventilation plays a dual role in formation of indoor pollutant concentrations: on one
hand it removes pollutants generated indoors from indoor spaces by ventilating the
space with outdoor air, on the other hand, ventilation introduces outdoor air pollutants
indoors [11, 12]. Assuming a constant outdoor pollution level and constant
penetration efficiency, increasing ventilation directly leads to increased indoor
exposures to outdoor pollutants. Even in the case of efficient filtering of particles in
the intake air, detailed studies have shown that a substantial fraction of the outdoor air
enters indoors via windows, doors, ventilation ducts, and cracks and leaks in the
building envelope, leading to much lower actual filtration efficiency [13].
Due to the counter-acting roles of indoor and outdoor air sources on indoor exposures,
a mass-balance model is needed to address it when defining prevailing indoor
concentrations. A commonly used approach based on Dockery and Spengler [14] and
adopted in Hänninen et al. [11], [15] is as follows:
Eq 1 )()( kat
C
kaV
GC
ka
PaC i
ai
where Ci is the total indoor concentration (µg m-3
) of the pollutant in question, Ca is
the concentration in the intake air, P is the probability of the pollutant remaining
suspended after penetrating through the building envelope, α is air exchange rate (h-1
),
k is the deposition rate of the pollutant indoors (h-1
), G is the indoor generation level
(µg h-1
), V is the volume and t is the temperature of the indoor space. The third term
covering the transient impacts of changing concentration can be considered zero for
the sake of long-term average exposures. Detailed input data and more details of
calculations are presented in Hänninen and Asikainen (2013) [16].
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Because the aim of this study is to estimate how changes in ventilation affect
exposures, the probability distributions of national ventilation rates in a building stock
of year 2010 had to be estimated. Surprisingly limited data of measured ventilation
rates are available for European countries. Due to this, available measured data was
reviewed and a regression model was created combining the climatological and
economical differences in the building stocks with ventilation rates. Further modelling
with a Bayesian subjective probability approach was used for generation of lognormal
probability distributions for ventilation rates in each EU-26 country (Table 1, method
described in detailed elsewhere [17]).
Table 1.
Risk model
Large number of indoor air pollutants has been associated with health responses, but
some of those either play a small role from the point of view of public health, or pose
challenges for the exposure assessment or quantification of the burden of disease.
Health determinants of housing in general are discussed in WHO 2011 [18], safe
levels of specific chemicals indoors in WHO 2010 [2] and guidelines for exposure to
dampness and mould specifically in WHO 2009 [1]. The current enhancement of the
health impact assessment with the above described mass-balance approach to account
for variable ventilation is built on the previous achievements of EnVIE [19] and
IAIAQ projects [20] and the corresponding models for environmental burden of
disease caused by indoor air quality. These models were based on a predefined
population attributable burden of disease (BoD) for each exposure and disease and
national estimates are then calculated from the national burden of disease data by
scaling the attributable fraction according to the ratio of national versus European
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indoor concentration estimates of each pollutant. (i.e. PM2.5, outdoor bioaerosols,
VOC, carbon oxide (CO) radon and dampness). In the current work the earlier PM2.5,
radon and dampness models were updated to the relative risk-based population
attributable fraction (PAF) approach but keeping the IAIAQ disease classification. In
addition, second hand smoke exposures at home were added using exposure data from
a European survey [21].
Exposures to environmental pollutants are associated with increased mortality and
morbidity. Traditional risk assessment methods estimate these separately as numbers
of cases. The results from such incidence-based models are not comparable over
different types of health endpoints and to improve comparability of impacts on
various types of diseases and including mortality, disability adjusted life years
(DALY) has been proposed as a common metric [22].
The burden of disease methodology makes the years of life lost (YLL) due to
premature mortality and years lived with a disability (YLD) comparable and is
summing them up as disability adjusted life years (DALY)
Eq 2 YLDYLLDALY
The disabilities caused by various types of diseases are calculated accounting for the
duration of the disease (L) and scaled using a disease specific disability weight (DW):
Eq 3 LDWYLD
In the current work the fraction of disease caused by the indoor exposures to various
pollutants is estimated using national statistics on the overall background burden of
the target diseases (Table 1) and calculating the population attributable fraction (PAF)
as [Error! Reference source not found.]:
Eq 4 1)1(
)1(
RRf
RRfPAF
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where f is the fraction of population exposed to a given factor and RR is the relative
risk of the exposed population. Now if the background burden of disease (BoD) is
known the environmental burden of disease (EBD) caused by the current exposures
(Table 2) can be calculated as
Eq 5 BoDPAFEBD
The relative risk at the current exposure level can be estimated from epidemiological
relative risk (RR°) expressed per a standard exposure increment, e.g. 10 µg m-3
:
Eq 6 ERRE RReRR ln
WHO estimates for national burden of disease in 2004 were used for the background
BoD [24]. Pollutant specific diseases and methodology are presented in Table 3.
Table 2.
Table 3.
Exposure control scenarios
Three alternative exposure control scenarios were evaluated using the mass-balance
enhanced burden of disease model to evaluate their efficiency to reduce BoD. The
exposure control scenarios start from optimizing the ventilation rates only. As it
proves inefficient, it is complemented firstly with control of filtration of outdoor
pollutants and secondly with control of indoor sources.
Dilution by optimal ventilation
The first exposure reduction scenario is defined as finding the health-based optimum
ventilation rate without any other actions that change indoor or outdoor sources. In
this scenario the pollutant concentrations from indoor and outdoor sources compete so
that pollutants from indoor sources are decreasing and pollutants from the outdoor
sources are increasing when the ventilation rate is increased. The health-based
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optimum level of ventilation is solved for each country among EU-26 by calculating
burden of disease with ventilation rates from 0.1 to 50 lps pp.
The calculations assume that all indoor originating exposures follow the mass-balance
dilution even though this is not self-evident for several indoor originating pollutants,
especially radon, dampness, mould and carbon monoxide. Radon infiltrates typically
from the soil below the buildings, and the infiltration may react to the under pressure
indoors, which may increase in some ventilation systems at higher ventilation rates.
Dampness may also be created by condensation and may thus increase at higher
ventilation rates. Carbon monoxide is lethal at high exposure levels and more efficient
dilution by higher ventilation may not be sufficient. However, for all these pollutants
the benefits of higher ventilation rates are calculated assuming the mass-balance for a
constant source term.
Filtration of intake air
Previous analyses of the sources of indoor exposures have shown that outdoor air is a
significant source of exposures. Therefore the second scenario was determined as an
attempt to control the burden of disease by filtration the exposures originating from
outdoor air. Because both ultrafine and coarse particles and chemically reactive
pollutants like ozone have lower infiltration factors than PM2.5, dominated by
accumulation mode particles, the filtration was specified for PM2.5 particles.
Three levels of filtration were compared. The baseline estimates assume that 90% of
the outdoor PM2.5 mass concentration penetrates indoors. In addition, realistic but
increasingly challenging penetration levels of 70% and 50% were evaluated. These
correspond to effective filtration of PM2.5 mass concentration by 27% and 45%,
respectively, filtration levels that can be achieved in real buildings at least when using
mechanical ventilation systems [13]. When discussing the filtration efficiencies of
filters and the above mentioned penetration efficiencies, it has to be noted that the
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penetration efficiency is defined for the building, accounting for leaks and ventilation
from windows, doors etc.
The health-based optimum ventilation was defined in this scenario also, and used
when calculating the burden of disease results and the reduction potential compared to
the baseline scenario.
Source control and minimum ventilation (4 lps pp)
The third approach to optimizing ventilation for health focuses first on indoor sources
of exposures. Now, instead of attempting to dilute these sources as they are, they are
first assumed to be controlled by other means as much as technically feasible before
optimizing the ventilation for health. The assumed control potentials for the
considered pollutants were:
• -90% for radon, carbon monoxide (CO) and second hand smoke (SHS)
• -50% for volatile organic compounds (VOC) and dampness
• -25% for particulate matter (PM2.5)
These hypothetical source controls were defined to approach maximum technically
feasible reductions. The radon estimate assumes efficient application and control of
radon safe construction in radon-prone areas combined with control of second hand
smoke exposures known to act synergistically with radon. Efficient second hand
smoke reductions have already been demonstrated in Finland in both workplaces and
in homes resulting a decrease in proportion of adolescents exposed to SHS from 17%
in 1991 to 6% in 2009 [25] and the SHS policies are moving forward also on at
European level. The carbon monoxide controls were aimed to be implemented by
compulsory alarms that will allow for identification of malfunctioning devices before
the risks occur.
VOC controls can be reached by comprehensive labelling systems for low emission
products. Dampness controls need to combine structural improvements with
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active/online and passive warning sensors. The most challenging element was
considered to be particulate matter. The proposed 25% reduction can be achieved with
target exhausts in kitchens, avoiding use of candles and improved design of
combustion devices.
To provide some sensitivity analysis to estimate the effectiveness of source control,
two other scenarios with lower and higher source control capabilities were also
analysed. In the lower source control scenario (scenario 3.1) it was assumed a
reduction of 80% for radon, CO and SHS and 25% reduction of PM2.5, VOC and
dampness exposures. In the higher source control scenario (scenario 3.2) a total
control (100%) of radon, CO and SHS and 75% reduction of PM2.5, VOC and
dampness exposures were assumed.
In all source control scenarios the ventilation level was set to be 4 lps pp, which was
defined as base ventilation rate in cases when ventilation must handle only human
bio-effluent emissions (carbon dioxide (CO2) and moisture) by work done in
HealthVent to define the health based ventilation requirements [26].
Results Attributable burden of disease in 2010
Exposures to indoor and outdoor originating pollutants were associated with a burden
of disease corresponding to an annual loss of 2.1 million DALYs in EU-26. More than
half of this burden (1.28 million DALYs) is caused by exposures to outdoor air
pollution indoors. The remaining 0.74 million DALYs are associated with pollutants
from various indoor sources.
The burden of disease caused by indoor exposures is dominated by cardiovascular
(CV) diseases; 45% of the total burden comes from CV-diseases associated with
outdoor particles, with an additional 12 % caused by indoor sources of exposures of
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particles and second hand smoke (Figure 1). Cardiovascular diseases are followed by
asthma (total of 12%) and lung cancer (23%). The remaining 8% is divided between
various respiratory symptoms and conditions.
Figure 1.
The total burden of disease for individual countries varies between 2000 and 10 000
DALYs per million (Figure 2). The highest burden in Bulgaria is almost five times
higher than that in Sweden. The higher levels in East-European countries are
dominated by high contributions from outdoor sources. The contribution of outdoor
sources varies between 46% (Ireland) to 75% (Bulgaria). The EU-26 average burden
corresponds to slightly over 4000 DALY in a year per one million population.
Figure 2.
Source contributions to burden of disease
Overall in EU-26, over 50% of the total annual burden of disease associated with
indoor exposures (4000 DALYs/million) is estimated to be caused by PM2.5
originating from outdoor air, followed by particles from indoor sources, and radon
(Figure 3).
The contribution of different sources to the total DALYs varies between countries.
This can be seen when comparing the sources of the burden of disease in Finland
(Figure 3) and in other EU-26 countries (Table 4) with the population-weighted mean
of EU-26 countries. It is readily apparent that in Finland the role of ambient particles
is lower than in Europe in general, but that both bio-aerosols (pollen) and radon play
much more significant roles. Especially the contribution of radon is double to that of
the European average, highlighting the geology peculiarities of the Finnish soil.
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However, in Finland the burden of disease from lung cancer caused by radon
exposures is alleviated partly by lower smoking prevalence. On average, 31% of over
15-year olds smoke daily or occasionally in EU countries and the smoking figures are
lower only in Finland (25%), Sweden (25%) and Slovakia (22%) [21].
Dampness and mould problems continuously raise a lot of attention in Finland, too.
Nevertheless, the burden of disease in Finland is from the lower end on the European
scale (ranging from 1% to 11%), and only 3% is estimated to be caused by dampness
in comparison with average of 5% in EU-26.
Figure 3.
Control scenario benefits including optimal ventilation
The burden of disease caused by indoor exposures, estimated above to be over 4 000
DALYs per year per a population of 1 million in EU-26, is significant. However, also
substantial reductions have been proposed in the earlier work within the EU funded
IAIAQ project [20]. The three alternative scenarios (and two additional source control
scenarios) described earlier were tested to support policy development for controlling
the risks and reducing the burden. The overall comparison of these scenarios in EU-26
is presented in Figure 4. The achievable health benefits were 20% for the dilution
scenario, 38% for the filtration scenario, and 44% for the indoor source control
scenario (changing from 41% to 54% depending on assumed source reductions).
Figure 4.
Each control scenario provides noteworthy health benefits. However, in the dilution-
based scenario 1 the health benefits remain smallest because the reduction of indoor
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originating exposures is compensated by infiltration of outdoor pollution when
increasing ventilation rates. The European health optimum (lowest burden of disease
achieved by changing national ventilation level) is found at mean ventilation level of
4.4 lps pp, which is clearly lower than the mean ventilation in the existing building
stock (17 lps pp) defined by the regression modelled probability distributions (Table
1) [16, 17].
Approximately twice as high benefits are achievable by filtration of outdoor air in
scenario 2. The results for maximum feasible filtration (with penetration fraction P =
50%) show that reduction in burden of disease approach 38 % or 800 000 DALYs in
EU-26. The European optimum mean ventilation level is then 7.7 lps pp. Health-
optimized ventilation level in addition to the filtration produces small additional
improvements. This scenario would in practice imply substantial change towards
mechanical ventilation systems in Europe. In the Nordic countries this is already the
practice due to the energy efficiency norms, but in the majority of the European
building stock the filtration scenario would require a substantial step towards
installing mechanical systems.
However, largest health benefits can be achieved by the source control approach
(scenario 3.0), which significantly reduces the need to control exposures by dilution.
The benefits are approximately 44% from the baseline, or 940 000 DALYs in EU-26,
and changing from reduction of 41% (865 000 DALY) with lower source control
assumptions to 57% (1.21 million DALY) with higher source control assumptions,
demonstrating source control to be more effective than dilution or filtration even with
smaller reductions of source exposures.
In addition to of higher health benefits, in comparison with the filtration-based
scenario 2 the advantage is that with source control the lower dilution need (i.e.
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enabling lower ventilation rate) allow also for lower infiltration of outdoor particles
and therefore the feasibility of the approach is better in the current building stock.
Moreover, with lower ventilation rates require the source control approach is likely to
prove also more energy-efficient.
Further analysis of the contribution of indoor and outdoor sources on these scenarios
shows, that with the dilution scenario the health benefits are not only due to smaller
proportion of the indoor contribution (i.e. the dilution of the pollutants from the
indoor sources) but is mainly based on the lower ventilation rates that actually limits
the penetration of the outdoor pollutants to indoors.
In the filtration scenario the health benefits are due to filtration of the outdoor
pollutants and also effective dilution of the indoor pollutants as the health-based
optimal ventilation levels are higher.
Also in the source control scenarios the health benefits are a result of both effects;
firstly by the lower indoor sources due to the source control and secondly by lower
penetration of outdoor pollutants due to low level of ventilation.
Discussion The results suggest that (i) there is a substantial burden of disease associated with
exposures through inhalation taking place indoors and that (ii) these risks can
substantially be reduced by various policies that include a range of control actions
affecting indoor pollution sources, infiltration of outdoor pollutants, and ventilation
levels. Besides the estimated health benefits and policy implementation costs, the
suggested prioritization of the policies depends also on the uncertainties of the
estimates.
Model uncertainties are causing the largest concerns here. They include the selection
of pollutants and health end-points associated with them. It is clear that in the current
- 17 -
context a substantial uncertainty is raised from here: it is not clear how much the
burden of disease estimates are underestimated due to the dozens of ignored
exposures or missing health endpoints for the included exposures. At best the model
uncertainties can and should be qualitatively judged by experts before the general
implementation of results.
Parameter uncertainties are easiest to estimate and evaluate. Quantification of the
exposure-response relationships and mass-balance model for exposures belong also to
the parameter uncertainties. Variable degree of uncertainty exists in the exposure-
response response relationships based on epidemiological studies. For some of the
included pollutants, like PM2.5 originating from outdoor air, this data is based on a
large number of studies, representing very large populations in different
climatological regions. The exposure-response relationship of ambient particles has
also been used for indoor generated particles. The indoor generated particles have
partly similar composition, originating from combustion processes or being re-
suspended particles originating from soil, for which it is reasonable to assume similar
toxicity as for the ambient particles. Some particle fractions, especially the particles
from cooking of food, from the occupants, and from textiles, have a different
chemical composition with limited direct evidence on their toxicity.
Scenario uncertainties are inherent for any future forecasts; we may not know all
changes in the systems under investigation and therefore must rely on assumptions.
When selecting policies for implementation, the implementation timeframe should
also be considered. Most significant element in the scenario uncertainties is related to
the development of future building stocks. The current ventilation guidelines are
intentionally formulated so that the focus is on the key parameters in terms of health,
the exposures, and there are as little as possible elements that require specific
- 18 -
technical solutions. An example of such an issue is the filtration of outdoor air
pollution, especially PM2.5, but also pollen, other biological particles, ozone, ultrafine
traffic particles and so on. Infiltration of ambient particles depends on air exchange
rates, size distribution of the outdoor particles, and filtration of the intake air. At
lower air exchange rates the prolonged residence time of air indoors and
corresponding deposition of particles on indoor surfaces reduces indoor exposures
even when the outdoor air is not filtrated. Using window frames and other
sedimentation chambers allows for filtrating particles even in natural ventilation
systems. Nevertheless, active filtration becomes efficient only in mechanical systems
using high quality (above FP7) filters.
The used ventilation rate estimates per occupant (lps pp) are calculated using average
residence sizes and average numbers of occupants in each country. Population
weighted average outdoor concentrations have also been used in estimating the indoor
exposures. It is clear that the air filtration needs for a specific building have to be
defined using the ambient air quality at the selected building location. In all countries
considered there are locations where the outdoor levels exceed the WHO guidelines
much more than the national averages used here indicate. When the current methods
proposed for determining the potential filtration needs, they have to be applied with
worst case estimates for the actual building site, accounting for the whole service life
cycle.
Largest health benefits were projected for the source control policies. It is obvious
that the benefits are achievable only if the source controls work as efficiently as
proposed and that the efficiency of the source controls must be confirmed with
follow-up (e.g. auditing) of exposure levels after the policy enforcement.
- 19 -
Conclusions Over 2 million disability adjusted life years (DALY) are annually lost in the European
Union due to compromised indoor air quality, but this burden of disease can be
reduced by adjusting ventilation, filtration of intake air and by controlling indoor
sources. All three approaches are able to provide substantial reductions in the health
risks from approximately 20 % to almost 50%, corresponding to 400 000 and 900 000
saved DALYs in EU-26. Thus selection of strategies has substantial impact on the
expected benefits.
The projected health benefits can be achieved if the controls on ventilation and
sources are fully implemented as defined in the scenario descriptions. In the case of
selecting some of the proposed strategies for implementation, a careful follow-up plan
has to be developed for ensuring that the controls are effective and match the
requirements of the benefit calculations.
List of abbreviations used BoD = burden of disease
CO = carbon monoxide
CO2 = carbon dioxide
CV = cardiovascular
DALY = disability adjusted life years
DW = disability weight
EBD = environmental burden of disease
EU = European Union
IAQ = indoor air quality
L = duration of the disease
lps pp = liters per second per person
- 20 -
PAF = population attributable fraction
PAQ = perceived air quality
PM2.5 = particulate matter sized < 2.5 mm
RR = relative risk
SARS = severe acute respiratory syndrome
SBS = sick building syndrome
SHS = second hand smoke
VOC = volatile organic compounds
WHO = World Health Organization
YLD = years lived with a disability
YLL = years of life lost
Competing interests The authors declare that they have no competing interests.
Authors' contributions AA carried out the modelling and calculation of results and drafted the manuscript.
PC participated on the literature review for the background section and in the design
of the study. EOF participated in the design of the study. SK participated in the design
of the study and helped to draft the manuscript. PW participated in the design of the
study, coordination and helped to draft the manuscript. OH participated on the design
of the calculations, coordination and helped to draft the manuscript. All authors read
and approved the final manuscript.
Funding This work has been supported by the EU Health Programme HEALTHVENT Grant
Nr. 2009 12 08, EU FP7 (TRANSPHORM), Academy of Finland (PM Sizex) and
Ministry of Social Affairs and Health project TEKAISU.
- 22 -
References 1. WHO: Dampness and mould. WHO Guidelines for Indoor Air Quality.
WHO Regional office for Europe, Copenhagen 2009, ISBN 798 92 890
4168 3. http://www.euro.who.int/document/E92645.pdf (accessed 2014-
08-22).
2. WHO: Guidelines for Indoor Air Quality: Selected pollutants. World
Health Organization, Regional Office for Europe, Copenhagen 2010,
Denmark. ISBN 978 92 890 0213 4.
3. WHO: Air quality guidelines for Europe. World Health Organization,
Regional Office for Europe, European series, No 23, Copenhagen 1987,
Denmark
4. WHO: Air quality guidelines for Europe; Second edition. World Health
Organization, Regional Office for Europe, No 91, Copenhagen 2000,
Denmark. http://www.euro.who.int/document/e71922.pdf (accessed 2014-
08-22).
http://www.euro.who.int/__data/assets/pdf_file/0009/128169/e94535.pdf
(accessed 2014-09-22
5. EN15251: CEN Standard on Indoor environmental input parameters for
design and assessment of energy performance of buildings- addressing
indoor air quality, thermal environment, lighting and acoustics. European
Committee For Standardization (CEN) 2007, Brussels. 52 pp
6. Wargocki P, Sundell J, Bischof W, Brundrett G, Fanger PO, Gyntelberg F,
et al: Ventilation and health in non-industrial indoor environments:
report from a European multidisciplinary scientific consensus meeting
(EUROVEN). Indoor Air 2002, 12: 113-128
- 23 -
7. Seppänen OA, Fisk WJ: Summary of human responses to ventilation.
Indoor Air 2004, 14 (Suppl 7):102–118
8. Li Y, Leung GM, Tang JW, Yang X, Chao CYH, Lin JZ, Lu JW, Nielsen
PV, Niu J, Qian H, Sleigh AC, Su H-JJ, Sundell J, Wong TW, Yuen PL.
Role of ventilation in airborne transmission of infectious agents in the
built environment – a multidisciplinary systematic review. Indoor Air
2007, 17: 2–18
9. Sundell J, Levin H, Nazaroff WW, Cain WS, Fisk WJ, Grimsrud DT,
Gyntelberg F, Li Y, Persily AK, Pickering AC, Samet JM, Spengler JD,
Taylor ST, Weschler CJ: Ventilation rates and health: multidisciplinary
review of the scientific literature. Indoor Air 2011, 21: 191-204
10. EEA: Air quality in Europe. European Environment Agency Report
9/2013, 2013, 112 pp. ISSN 1725-9177
http://www.eea.europa.eu/publications/air-quality-in-europe-
2013/at_download/file (accessed 2015-01-30)
11. Hänninen O, Lebret E, Ilacqua V, Katsouyanni K, Künzli N: Infiltration
of ambient PM2.5 and levels of indoor generated non-ETS PM2.5 in
residences of four European cities. Atmos. Environ. 2004, 38: 6411-6423
12. Hänninen OO, Palonen J, Tuomisto JT, Yli-Tuomi T, Seppänen O,
Jantunen MJ, et al.: Reduction potential of urban PM2.5 mortality risk
using modern ventilation systems in buildings. Indoor Air 2005, 15:
246-256 doi:10.1111/j.1600-0668.2005.00365.x
13. Fisk WJ, Faulkner D, Palonen J, Seppänen O: Performance and costs of
particle air filtration technologies. Indoor Air 2002, 12: 223-234
- 24 -
14. Dockery DW, Spengler JD: Personal exposure to respirable particulates
and sulfates. J. Air Pollut. Control Assoc. 1981, 31: 153-159
15. Hänninen O, Sorjamaa R, Lipponen P, Cyrys J, Lanki T, Pekkanen J:
Aerosol-based modelling of infiltration of ambient PM2.5 and
evaluation against population-based measurements in homes in
Helsinki, Finland. J. Aerosol Sci. 2013, 66:111-122
16. Hänninen O, Asikainen A (eds.): Efficient reduction of indoor exposures:
Health benefits from optimizing ventilation, filtration and indoor source
controls. National Institute for Health and Welfare (THL). Report 2/2013.
Helsinki 2013. ISBN 978-952-245-821-6 (printed) ISBN 978-952-245-
822-3 (online publication) http://urn.fi/URN:ISBN:978-952-245-822-3
17. Asikainen A, Hänninen O, Brelih N, Bischof W, Hartmann T, Carrer P,
Wargocki P: Proportion of residences in European countries with
ventilation rates below the regulation based limit value. Int J. Vent.
2013, 12: 129-134
18. WHO: Environmental burden of disease associated with inadequate
housing. World Health Organization, Regional Office for Europe,
Copenhagen 2011, Denmark
http://www.euro.who.int/__data/assets/pdf_file/0003/142077/e95004.pdf
(accessed 2014-08-22)
19. Oliveira Fernandes de E, Jantunen M, Carrer P, Seppänen O, Harrison P,
Kephalopoulos S: Co-ordination Action on Indoor Air Quality and Health
Effects (ENVIE). Final report, 2009,
http://paginas.fe.up.pt/~envie/documents/finalreports/Final%20Reports%2
- 25 -
0Publishable/Publishable%20final%20activity%20report.pdf (accessed
2014-08-22)
20. Jantunen M, de Oliveira Fernandes E, Carrer P, Kephalopoulos S:
Promoting actions for healthy indoor air (IAIAQ). European Commission
Directorate General for Health and Consumers. Luxembourg 2011. ISBN
978-92-79-20419-7.
http://ec.europa.eu/health/healthy_environments/docs/env_iaiaq.pdf
(accessed 2014-08-22)
21. EC: Survey on Tobacco. Analytical report. European Commission Flash
Eurobarometer 253, 2009
http://ec.europa.eu/public_opinion/flash/fl_253_en.pdf (accessed 2014-08-
22).
22. Murray CJ, Lopez AD: Alternative projections of mortality and
disability by cause 1990-2020: Global Burden of Disease Study. Lancet
1997, 349: 1498-1504. doi:10.1016/S0140-6736(96)07492-2
23. Hänninen O, Knol A (eds.): European perspectives on Environmental
Burden of Disease; Estimates for nine stressors in six countries. THL
Reports 1/2011, Helsinki 2011, Finland. ISBN 978-952- 245-413-3.
http://urn.fi/URN:NBN:fi-fe201205085022 (accessed 2015-02-12)
24. WHO: The global burden of disease 2004 update. World Health
Organization, Regional Office for Europe, 2008, Switzerland
http://www.who.int/healthinfo/global_burden_disease/GBD_report_2004u
pdate_full.pdf
25. Raisamo SU, Doku DT, Heloma A, Rimpelä AH: Persistence of
socioeconomic differences in adolescents’ environmental tobacco
- 26 -
smoke exposure in Finland: 1991–2009. Scandinavian Journal of Public
Health 2014, 42: 184–193.
26. ECA: Guidelines for health-based ventilation in Europe (HealthVent).
Report nr 30 of European Collaborative Action (ECA), Urban Air, Indoor
Environment And Human Exposure. Environment and Quality of Life, EC
Joint Research Centre 2015, Ispra, Italy
27. Pope CA, Burnett RT, Thun MJ, Calle EE, Krewski D, Ito K, et al.: Lung
cancer, cardiopulmonary mortality, and long-term exposure to fine
particulate air pollution. JAMA 2002, 287: 1132-1141
28. Darby S, Hill D, Auvinen A, BarrosDios JM, Baysson H, Bochicchio F,
Deo H, et al.: Radon in homes and lung cancer risk: collaborative
analysis of individual data from 13 European case control studies.
British Medical J. 2005, 330: 223–226
29. Fisk WJ, Lei-Gomez Q, Mendell MJ: Meta-analyses of the associations
of respiratory health effects with dampness and mold in homes. Indoor
Air 2007, 17: 284-296
30. US Surgeon General: The health consequences of involuntary exposure to
tobacco smoke. A Report of the Surgeon General Office on Smoking and
Health, Centers for Disease Control and Prevention, Atlanta 2006, US
http://www.ncbi.nlm.nih.gov/books/NBK44324/ (accessed 2015-02-12)
31. Jaakkola MS, Piipari R, et al.: Environmental tobacco smoke and adult-
onset asthma: a population-based incident case-control study. Am J
Public Health 2003, 93: 2055-60
- 27 -
Figure legends
Figure 1. Attributable burden of diseases due to indoor exposures in 2010 in EU-26. The lighter shade represents the maximum fraction that can be reduced by actions (scenarios) presented in this paper
Figure 2. Total burden of disease as DALY/million population from indoor exposures in EU-26 countries with division to indoor and outdoor sources in the 2010 building stock
Figure 3. Burden of disease attributable to indoor exposures in EU-26 (2.1 M DALY/a) and in Finland (13 k DALY/a) in 2010 divided into source contributions.
Figure 4. Burden of disease at the baseline (2010) in comparison with alternative potential control strategies in EU-26 (in millions of DALYs).
- 28 -
Tables Table 1. Estimated ventilation rate distributions in European countries [17].
Air exchange rate Ventilation rate per occupant
Country Mean Median One-GSD
Mean Median One-GSD
rangea range
a
h-1
h-1
h-1
lps pp lps pp lps pp
Austria 0,9 0,7 (0.4-1.3) 25 21 (11.1-39.1)
Belgium 0,7 0,6 (0.3-1.1) 17 14 (7.6-26.7)
Bulgaria 0,7 0,6 (0.3-1.1) 15 12 (6.4-22.3)
Cyprus 1,2 1,0 (0.5-1.9) 24 20 (10.6-37.2)
Czech Republic 0,6 0,5 (0.3-1.0) 14 11 (6.0-21.1)
Denmark 0,7 0,5 (0.3-1.0) 24 20 (10.4-36.6)
Estonia 0,7 0,5 (0.3-1.0) 13 10 (5.5-19.4)
Finland 0,7 0,5 (0.3-1.0) 17 14 (7.5-26.3)
France 0,6 0,5 (0.3-1.0) 18 14 (7.7-27.1)
Germany 0,7 0,6 (0.3-1.0) 20 17 (8.8-31.0)
Greece 1,0 0,8 (0.4-1.5) 20 17 (8.8-30.9)
Hungary 0,8 0,6 (0.3-1.2) 16 13 (6.8-24.0)
Ireland 0,6 0,5 (0.3-0.9) 14 12 (6.2-21.9)
Italy 0,8 0,6 (0.3-1.2) 21 17 (9.2-32.4)
Latvia 0,7 0,5 (0.3-1.0) 11 9 (4.9-17.2)
Lithuania 0,7 0,6 (0.3-1.0) 11 9 (4.9-17.3)
Luxembourg 0,9 0,7 (0.4-1.3) 32 26 (14.1-49.5)
Netherlands 0,7 0,6 (0.3-1.0) 21 17 (9.1-32.1)
Poland 0,7 0,6 (0.3-1.1) 11 9 (4.8-16.7)
Portugal 0,7 0,6 (0.3-1.1) 15 12 (6.6-23.1)
Romania 0,8 0,6 (0.3-1.2) 7 6 (3.2-11.1)
Slovakia 0,8 0,6 (0.3-1.2) 12 10 (5.1-17.9)
Slovenia 0,7 0,6 (0.3-1.1) 13 11 (5.9-20.7)
Spain 0,8 0,7 (0.3-1.2) 20 17 (8.9-31.3)
Sweden 0,6 0,5 (0.3-1.0) 20 17 (9.0-31.5)
UK 0,6 0,5 (0.3-0.9) 15 13 (6.8-23.8)
EU-26 0,7 0,6 (0.3-1.1) 17 14 (7.3-25.6)
- 29 -
Table 2. Outdoor and indoor exposure levels (PM2.5, radon and VOC) and prevalence of exposure (dampness in homes and second hand smoke of non-smoking population) in European countries used for burden of disease calculations.
Out.
PM2.5
Ind.
PM2.5
Out.
VOC
Ind.
VOC
Ind.
Radon
Dampness
homes
SHS non-
smokers
µg m-3 µg m-3 µg m-3 µg m-3 Bq m-3 % %
Austria 17 5 103 298 97 8 14
Belgium 19 5 103 298 69 14 18
Bulgaria 22 5 103 298 30 n/a 23
Cyprus 23 4 103 298 7 30 31
Czech Republic 23 5 116 334 140 16 16
Denmark 13 3 103 298 53 11 17
Estonia 11 3 103 298 120 23 16
Finland 9 3 64 226 120 5 2
France 12 5 77 223 89 14 9
Germany 16 5 103 297 50 13 13
Greece 21 4 155 345 55 19 28
Hungary 25 5 103 298 107 19 12
Ireland 8 3 103 298 89 15 14
Italy 20 4 181 489 70 21 11
Latvia 12 3 103 298 0 26 12
Lithuania 14 3 103 298 55 25 28
Luxembourg 12 5 52 148 115 15 8
Netherlands 19 5 46 134 30 18 15
Poland 22 5 103 298 49 37 21
Portugal 18 4 38 213 86 20 13
Romania 23 5 103 298 45 29 23
Slovakia 23 5 103 298 87 6 13
Slovenia 17 5 103 298 87 17 14
Spain 16 4 103 298 90 18 20
Sweden 10 3 77 223 108 6 3
UK 13 3 85 245 20 15 7
EU-26 17 4 104 297 64 18 14
- 30 -
Table 3. Diseases and exposure-response relationships included in this
assessment.
Exposuresa
Health endpoints WHO RR PAF RR & PAF source(s)
BoD calculationb
PM2.5 Asthma W113 –c f(RR, E)
d Pope et al. 2002 PAF(E, RR) × BoD2004
Lung cancer W067 –c f(RR, E)
d Pope et al. 2002 PAF(E, RR) × BoD2004
CV-diseases W104 –c f(RR, E)
d Pope et al. 2002 PAF(E, RR) × BoD2004
COPD W112 –c f(RR, E)
d Pope et al. 2002 PAF(E, RR) × BoD2004
Outdoor bioaerosols
Asthma W113 –c 0.1
e Jantunen et al.,
2010 [20] PAF × BoD2004
VOC Asthma W113 –c 0.05 Jantunen et al.,
2010 [20] C/CEU × PAF × BoD2004
CO Acute toxication caused by carbon monoxide
n/a –c 0.9 Jantunen et al.,
2010 [20] Cases x 20 years lost/case
Radon Lung cancer W067 0.0014 f(RR, E)d Darby et al., 2005
[ PAF(E, RR) × BoD2004
Home dampness Respiratory infections W038 1.37 f(RR, E)d Fisk et al., 2007 PAF(E, RR) × BoD2004
Asthma W113 1.5 f(RR, E)d Fisk et al., 2007 PAF(E, RR) × BoD2004
SHSf Lung cancer W067 1.21 f(RR, E)
d US S.G. 2006 PAF(E, RR) × BoD2004
Ischaemic heart disease
W107 1.27 f(RR, E)d US S.G. 2006 PAF(E, RR) × BoD2004
Asthma W113 1.97 f(RR, E)d Jaakkola et al.,
2003 PAF(E, RR) × BoD2004
a Population weighted average in EU26
b C = National population weighted concentration, CEU = European average
concentration, E = National population weighted exposure
c Expert judgment PAF from the EnVIE panel used directly [19], see column PAF
d Calculated as PAF=(f×(RR-1))/((f×(RR-1))+1), where RR = RR°E [Error!
Reference source not found.].
e Original value of 0.25 in Jantunen et al. (2010) [20] adjusted to 0.1 due to separation
of indoor and outdoor sources and focusing on pollen from outdoor air
f Second hand smoke exposure of non-smoking adults at home.
- 31 -
Table 4. Contribution (%) of different sources to the total DALYs in 2010.
Ind.
PM2.5 Radon
Ind.
VOC CO Damp. SHS
Out.
PM2.5
Bio-
aeros
ols
Out.
VOC
Austria 18 11 1 1 1 5 58 3 0
Belgium 18 9 1 0 4 4 60 3 0
Bulgaria 17 2 0 0 3 2 74 1 0
Cyprus 11 0 1 0 11 12 61 3 0
Czech Republic 14 12 1 4 3 3 61 2 0
Denmark 13 9 2 3 3 6 59 5 1
Estonia 14 13 1 5 8 4 52 3 0
Finland 16 16 2 4 3 2 50 7 1
France 20 18 2 0 5 2 46 6 1
Germany 20 6 1 1 3 4 60 3 0
Greece 14 6 1 1 4 5 68 2 0
Hungary 15 12 0 1 1 1 69 1 0
Ireland 13 12 4 2 11 12 34 11 1
Italy 14 9 2 1 4 3 64 3 1
Latvia 15 6 1 2 7 3 64 2 0
Lithuania 14 5 0 0 6 10 63 1 0
Luxembourg 21 15 1 1 6 3 47 5 0
Netherlands 18 4 1 1 6 5 61 5 0
Poland 15 5 1 1 6 3 66 2 0
Portugal 14 7 1 1 7 4 62 4 0
Romania 16 3 0 1 7 2 70 1 0
Slovakia 16 7 1 1 2 3 70 2 0
Slovenia 17 11 1 2 5 3 56 3 0
Spain 14 14 1 0 5 4 57 4 0
Sweden 16 15 2 2 3 3 54 6 1
United 13 3 2 1 8 5 59 8 1
EU-26 16 8 1 1 5 4 62 3 0
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